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Feature

Review comment categories before they become official outputs

Review and correct student comment categories and sentiment before final reports, dashboards, and exports are generated.

Student Voice Analytics supports a review workflow for comment categories and sentiment. Staff can inspect the classification for a comment or sentence, correct it where needed, and regenerate outputs from the reviewed data.

Discuss your survey

Discuss the source data, reporting question, outputs and delivery window.

Who this is for

Survey teams, analysts, academic reviewers, and governance leads.

Why it matters

Automated classification can handle volume, but institutions still need a route for expert judgement. Review workflows stop edge cases, sensitive phrasing, or local context from being locked into final reporting without inspection.

What teams get

Bring expert judgement into the workflow

Academic and professional staff can check category fit for comments where local context or domain knowledge matters.

Correct once, then regenerate clean outputs

Corrections can feed updated workbooks, summaries, and dashboards rather than sitting in a separate manual note.

Support future consistency

Reviewed examples help teams understand classification boundaries and support better consistency across survey cycles.

How it works

  1. Open the review view from a comment, category, or report line.
  2. Inspect the sentence split, category label, and sentiment label.
  3. Apply corrections or notes where the reviewer disagrees.
  4. Regenerate the relevant outputs from the reviewed data.

Outputs

Governance and evidence quality

FAQs

Can a single comment have more than one category?

Yes. Sentence-level analysis can handle comments that mention more than one issue or contain both positive and negative signals.

Do corrections affect the final reports?

Yes. Corrections can be incorporated before reports and exports are regenerated.

Who should review categorisation?

The best reviewers are usually survey leads, quality staff, local academic leads, or service owners who understand the context behind the comments.

See the workflow with your team

Discuss the source data, reporting question and outputs your team needs. Explore the worked example before agreeing the scope and delivery window.

Discuss your survey